Electronic Device Image Luminance Adjustment via HVS Histogram Analysis
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Solution Overview
Problem
Electronic devices with limited high-luminance output fail to consider human visual system (HVS) recognition and image features, resulting in reduced dynamic range and image distortion.
Innovation Solution
An electronic device with a processor that stores HVS recognition information and uses histogram analysis to adjust image gradation and luminance, applying tone mapping curves and weight matrices to optimize output within maximum luminance constraints, minimizing visual differences and distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If luminance is reduced to match limited high-luminance output, then output luminance is adjusted, but dynamic range width is reduced and image distortion occurs
Solution Approach 1:
The patent changes the luminance parameter dynamically based on local image characteristics and HVS recognition. Instead of uniform luminance reduction, the system adjusts luminance values pixel-by-pixel or region-by-region, transforming the single parameter approach into a multi-parameter adaptive approach that preserves image quality while matching output capabilities.
Solution Approach 2:
The patent applies different luminance adjustment strategies to different regions of the image based on local characteristics. By analyzing local image features and HVS recognition at each pixel or region, the system applies tailored luminance transformations rather than global uniform adjustment, thereby maintaining overall image quality while adapting to limited output luminance.
2Illumination intensity
If uniform luminance reduction is applied, then output luminance is controlled, but image distortion according to HVS recognition occurs
Solution Approach 1:
The system transforms uniform luminance reduction into spatially-varying luminance adjustment by incorporating HVS recognition parameters. Each pixel or region undergoes luminance transformation based on its specific characteristics and HVS sensitivity, changing from a single parameter control to a field-dependent parameter control that eliminates uniform distortion.
Solution Approach 2:
The patent incorporates HVS recognition as a feedback mechanism to guide luminance adjustment. By continuously referencing HVS recognition information during the luminance transformation process, the system adapts its output to match human visual perception, thereby preventing distortions that would be perceptible to viewers.
3Device complexity
If simple luminance reduction is used, then device complexity is low, but image quality and HVS recognition are not considered
Solution Approach 1:
The patent segments the image processing into distinct functional stages: histogram analysis, HVS recognition information generation, luminance transformation, and tone mapping. By dividing the complex processing into modular segments, the system achieves high image quality through sophisticated algorithms while maintaining manageable device complexity through structured implementation.
Solution Approach 2:
The system performs preliminary analysis of image characteristics and generates HVS recognition information before applying luminance transformation. By preparing necessary data structures, histograms, and recognition parameters in advance, the patent enables complex adaptive processing without requiring excessive real-time computational complexity during actual image output.
Data Source
AI summary
Disclosed is an electronic device. The electronic device obtains a first histogram regarding a difference in gradation between adjacent pixels of an input image based on the first maximum output brightness, obtains a second histogram regarding a difference in gradation between the adjacent pixels of the input image based on the second maximum output brightness, obtains a third histogram regarding a difference in brightness between the adjacent pixels of the input image based on the first HVS recognition information, obtains a fourth histogram regarding a difference in brightness between the adjacent pixels of the input image based on the second HVS recognition information, and obtains a brightness value regarding the input image corresponding to the second maximum output brightness based on a difference between a first value obtained based on information on the first and third histograms and a second value obtained based on the second and fourth histograms.